A hydro-meteorological observation data acquisition and storage method, device, medium and product
By adopting standardized data tables and observation element information tables in the marine observation system, the problems of poor system scalability and stability were solved, and efficient and automated processing of hydrological and meteorological observation data was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- STATE OCEAN TECH CENT
- Filing Date
- 2026-05-08
- Publication Date
- 2026-06-02
Smart Images
Figure CN122132416A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of marine hydrological and meteorological observation data processing technology, and in particular to a method, device, medium and product for acquiring and storing hydrological and meteorological observation data. Background Technology
[0002] Currently, automatic observation systems at marine observation stations typically consist of a field data acquisition subsystem and a data center receiving and processing subsystem, with meteorological and hydrological equipment uploading observation data on a minute-by-minute basis. However, existing automatic observation systems at marine observation stations require separate development of storage and query interfaces for different observation elements. Adding new observation elements involves significant modifications, resulting in poor system scalability and stability, ultimately leading to low overall processing efficiency for hydrological and meteorological observation data. Therefore, providing a more scalable, stable, and efficient hydrological and meteorological observation data storage and retrieval solution has become a pressing technical problem in this field. Summary of the Invention
[0003] The purpose of this application is to provide a method, device, medium and product for acquiring and storing hydrological and meteorological observation data, which can improve the scalability and stability when adding new observation elements and improve the processing efficiency of hydrological and meteorological observation data.
[0004] To achieve the above objectives, this application provides the following solution.
[0005] In the first aspect, this application provides a method for acquiring and storing hydrological and meteorological observation data, including the following steps.
[0006] A standardized data table is established according to the preset observation element type and observation element day boundary. The standardized data table adopts a unified field naming rule and storage structure, and each observation station and each day boundary period corresponds to one record of observation data. The standardized data table includes: observation station code, observation date, observation value at the hour, maximum data and corresponding observation time within the day boundary period, minimum data and corresponding observation time within the day boundary period, and all observation data within the day boundary period.
[0007] Based on the standardized data table, an observation element information table is established; the observation element information table is used to configure the storage name, data format, observation element type, default data filling rules, and data access method of each observation element.
[0008] Receive data processing instructions; the data processing instructions include data storage instructions or data query and retrieval instructions.
[0009] When the data processing instruction is the data storage instruction, the hydrological and meteorological observation data to be processed is obtained, and the hydrological and meteorological observation data to be processed is stored based on the observation element information table to obtain the stored hydrological and meteorological observation data.
[0010] When the data processing instruction is the data query and retrieval instruction, the stored hydrological and meteorological observation data is queried and retrieved based on the observation element information table to obtain the data query and retrieval result.
[0011] Optionally, the types of observation elements include: meteorological observation elements and hydrological observation elements. The meteorological observation elements include: wind direction, wind speed, air temperature, relative humidity, air pressure, rainfall, and visibility. The hydrological observation elements include: surface seawater temperature, surface seawater salinity, and tidal level. The observation element boundaries include: meteorological boundary and hydrological boundary.
[0012] Optionally, the observation value field at the hour is named according to the order of the observation element type and the observation element's day boundary. All observation data fields within the day boundary period are stored in rows by hour, with each row starting with an hour identifier and adjacent observation values separated by spaces.
[0013] Optionally, when the data processing instruction is the data storage instruction, the hydrological and meteorological observation data to be processed is obtained, and the hydrological and meteorological observation data to be processed is stored based on the observation element information table to obtain the stored hydrological and meteorological observation data, specifically including the following steps.
[0014] Based on the data storage instructions, the hydrological and meteorological observation data to be processed is obtained.
[0015] The hydrological and meteorological observation data to be processed is divided into data packages and verified to obtain verified data.
[0016] The verified data is parsed to obtain the parsed observation information, which includes: observation station code, observation element name, observation time, and observation value.
[0017] Based on the parsed observation information and the observation element information table, the hydrological and meteorological observation data to be processed is stored and updated to obtain the stored hydrological and meteorological observation data.
[0018] Optionally, based on the parsed observation information and the observation element information table, the hydrological and meteorological observation data to be processed is stored and updated to obtain the stored hydrological and meteorological observation data, specifically including the following steps.
[0019] Based on the observation element names in the parsed observation information, query and match the corresponding observation element types in the observation element information table.
[0020] Based on the type of observation element queried and matched, determine whether to shift the date of the observation time in the parsed observation information to the date horizon, and obtain the first determination result.
[0021] If the first judgment result is yes, then add 1 day to the observation time in the parsed observation information to obtain the updated observation time.
[0022] If the first judgment result is negative, then the observation time in the parsed observation information is directly used as the updated observation time.
[0023] Based on the updated observation time, the names of observation elements and the observation station codes in the parsed observation information, the existence of the observation record for the day is queried and determined to obtain a second determination result.
[0024] If the second judgment result is yes, then read the data that has been stored in all observation data fields within the day's observation record during the day's period.
[0025] If the second judgment result is negative, then all observation data fields within the day period are initialized and filled according to the default data filling rules in the observation element information table.
[0026] Based on the number of data bits, decimal places, and the updated observation time in the observation element information table, calculate the storage location of the observed value in the parsed observation information within all observation data fields of the day cycle.
[0027] The observed values in the parsed observation information are formatted according to the number of data bits and the number of decimal places to obtain formatted observation values.
[0028] Based on the storage location, the formatted observation values are replaced in the corresponding storage location to update all observation data fields within the day period. At the same time, the observation value field at the hour, the maximum data and corresponding observation time field within the day period, and the minimum data and corresponding observation time field within the day period are updated synchronously to obtain the stored hydrological and meteorological observation data.
[0029] Optionally, when the data processing instruction is the data query and retrieval instruction, the stored hydrological and meteorological observation data is queried and retrieved based on the observation element information table to obtain the data query and retrieval result, specifically including the following steps.
[0030] Based on the data query and retrieval instruction, the data query conditions are determined; the data query conditions include the observation station code, the name of the observation element, the query date and / or the query type; the query type includes: hourly data, full minute data or specified minute data.
[0031] Based on the observation feature name, query the corresponding observation feature type and data format in the observation feature information table.
[0032] The corresponding date cycle is determined based on the observed element type and the query date, and the observation record corresponding to the date cycle is located.
[0033] Based on the query type, the corresponding data in the observation record is read to obtain the data query result.
[0034] Optionally, based on the query type, the corresponding data in the observation record is read to obtain the data query result, specifically including the following steps.
[0035] When the query type is the hourly data, the data in the observation value field corresponding to the hourly time in the observation record is read as the data query result.
[0036] When the query type is the full minute data, the data in all observation data fields within the day period of the observation record is read and used as the data query result.
[0037] When the query type is the specified minute data, the data position is calculated based on the query date, the observation element's day boundary, and the data format. Then, based on the data position, the corresponding minute data is extracted from all observation data fields within the day boundary period as the data query result.
[0038] Secondly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the hydrological and meteorological observation data acquisition and storage method described in any one of the above-mentioned methods.
[0039] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the hydrological and meteorological observation data acquisition and storage method described in any one of the above.
[0040] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the hydrological and meteorological observation data acquisition and storage method described in any one of the above descriptions.
[0041] According to the specific embodiments provided in this application, this application has the following technical effects.
[0042] This application provides a method, device, medium, and product for acquiring and storing hydrological and meteorological observation data. On the one hand, by establishing a standardized data table based on the preset observation element types and observation element diurnal boundaries, the standardized data table adopts a unified field naming rule and storage structure. Each observation station and each diurnal cycle corresponds to one record of observation data, encompassing various information such as observation station code, observation date, observation value at the hour, maximum data and corresponding observation time within the diurnal cycle, minimum data and corresponding observation time within the diurnal cycle, and all observation data within the diurnal cycle. This standardizes the field content of each observation element data table, making each observation element regular, which is conducive to writing a unified data entry and data acquisition interface, and improving the scalability and stability when adding new observation elements. On the other hand, by further constructing an observation element information table based on the standardized data table, which is used to configure the storage name, data format, observation element type, default data filling rules and data access methods of each observation element, data storage and data retrieval can be performed according to the observation element information table. It can quickly query the storage location, observation element type and data access methods of each observation element, etc., realize the automated processing of hydrological and meteorological observation data, and effectively improve the processing efficiency of hydrological and meteorological observation data. Attached Figure Description
[0043] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0044] Figure 1 An application environment diagram for a hydrological and meteorological observation data acquisition and storage method provided in an embodiment of this application; Figure 2 A flowchart illustrating a method for acquiring and storing hydrological and meteorological observation data according to an embodiment of this application; Figure 3 A schematic diagram showing part of the data storage of temperature observation elements on March 1, 2024, provided in an embodiment of this application; Figure 4 A schematic diagram showing part of the data storage of wind speed and wind direction observation elements on March 18, 2024, provided in an embodiment of this application; Figure 5A schematic diagram showing part of the data storage of tide level observation elements on March 18, 2024, provided in an embodiment of this application; Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation
[0045] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0046] Currently, the marine observation and forecasting system consists of a marine observation network, a data transmission network, a forecasting system, an information service system, and a disaster assessment system. Its main function is to collect and transmit hydrological and meteorological observation elements, and to produce and distribute forecast information products. The marine observation network comprises automatic hydrological and meteorological observation systems at marine observation stations, buoys, hydrological and meteorological observation systems on volunteer / survey vessels, radar, seabed bases, and underwater moorings. Its main function is to collect hydrological and meteorological observation elements on-site, providing data for the production of forecast information products. The data transmission network uses communication methods such as fiber optics, satellite, and CDMA / GPRS to transmit data and distribute products. The forecasting system provides forecast products using a combination of empirical statistics and numerical forecasting. The information system provides information products and services to users. The disaster assessment system provides disaster assessment results. The automatic hydrological and meteorological observation systems at marine observation stations within the marine observation network consist of an on-site acquisition system and a data center receiving and processing subsystem. The on-site acquisition system includes a meteorological subsystem and a hydrological subsystem, which transmit observation data to the data center once per minute via communication methods such as fiber optics, satellite, CDMA, or GPRS. The meteorological subsystem primarily observes wind direction, wind speed, air temperature, relative humidity, air pressure, rainfall, and visibility. The diurnal boundary for meteorological observations, according to observation specifications, is from 20:00 on the current day to 20:00 on the following day, excluding the hourly value at 20:00 on the current day. The hydrological subsystem primarily observes surface seawater temperature, surface seawater salinity, and tides. The diurnal boundary for hydrological observations, according to observation specifications, is from 00:00 on the current day to 00:00 on the following day, excluding the hourly value at 00:00 on the following day. After receiving data from the meteorological and hydrological subsystems, the data center parses and stores the data, and generates minute data files, hourly data files, and a monthly delayed report file for all observation elements at each station based on the stored data. The existing data center receiving software requires writing interfaces for data storage and querying for each observation element. When new observation elements are added, the software interface requires significant modifications, making expansion difficult and system stability hard to guarantee. The embodiments of this application aim to formulate and write standardized interface methods for data storage and data acquisition based on the characteristics of the day boundary of the meteorological subsystem and the hydrological subsystem and the characteristics of observation data. When new observation elements are added, the expansion is easy, the amount of code modification is small, and the system stability is high.
[0047] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0048] The hydrological and meteorological observation data acquisition and storage method provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on other servers. Terminal 102 can send hydrological and meteorological observation data to be processed to server 104. After receiving the hydrological and meteorological observation data, server 104 establishes a standardized data table according to preset observation element types and observation element boundaries; based on the standardized data table, it establishes an observation element information table; it receives data processing instructions; when the data processing instruction is a data storage instruction, it stores the hydrological and meteorological observation data to be processed based on the observation element information table, obtaining the stored hydrological and meteorological observation data; when the data processing instruction is a data query instruction, it performs a data query on the stored hydrological and meteorological observation data based on the observation element information table, obtaining the data query result. Server 104 can feed back the obtained data query result to terminal 102. In addition, in some embodiments, the hydrological and meteorological observation data acquisition and storage method can also be implemented by the server 104 or the terminal 102 separately. For example, the terminal 102 can directly perform data acquisition and storage processing on the hydrological and meteorological observation data to be processed, or the server 104 can obtain the hydrological and meteorological observation data to be processed from the data storage system and perform data acquisition and storage processing on the hydrological and meteorological observation data to be processed.
[0049] The terminal 102 can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, and IoT devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers, or it can be a cloud server.
[0050] In one exemplary embodiment, such as Figure 2 As shown, a method for acquiring and storing hydrological and meteorological observation data is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the following steps are included.
[0051] S1: Establish a standardized data table according to the preset observation element types and observation element boundaries. The standardized data table adopts a unified field naming rule and storage structure, and each observation station and each boundary period corresponds to one record of observation data. The standardized data table includes: observation station code, observation date, observation value at the hour, maximum data and corresponding observation time within the boundary period, minimum data and corresponding observation time within the boundary period, and all observation data within the boundary period.
[0052] S2: Based on the standardized data table, establish an observation element information table. This table is used to configure the storage name, data format, observation element type, default data filling rules, and data access method for each observation element.
[0053] S3: Receive data processing instructions; the data processing instructions include data storage instructions or data query and retrieval instructions.
[0054] S4: When the data processing instruction is the data storage instruction, the hydrological and meteorological observation data to be processed is obtained, and the hydrological and meteorological observation data to be processed is stored based on the observation element information table to obtain the stored hydrological and meteorological observation data.
[0055] S5: When the data processing instruction is the data query and retrieval instruction, the stored hydrological and meteorological observation data is queried and retrieved based on the observation element information table to obtain the data query and retrieval result.
[0056] By implementing steps S1 to S5 above, a standardized data table is established based on the preset observation element types and observation element day boundaries. This standardizes the field content of each observation element data table, making each observation element regular and facilitating the development of a unified data entry and data retrieval interface, thereby improving the scalability and stability when adding new observation elements. By constructing an observation element information table based on the standardized data table, and configuring the storage name, data format, observation element type, default data filling rules, and data access methods for each observation element, efficient data storage and data retrieval can be achieved based on the observation element information table. This realizes automated processing of hydrological and meteorological observation data and effectively improves the processing efficiency of hydrological and meteorological observation data.
[0057] As an optional implementation, in step S1, the types of observation elements include: meteorological observation elements and hydrological observation elements. The meteorological observation elements include: wind direction, wind speed, air temperature, relative humidity, air pressure, rainfall, and visibility. The hydrological observation elements include: surface seawater temperature, surface seawater salinity, and tidal level. The observation element diurnal boundaries include: meteorological diurnal boundaries and hydrological diurnal boundaries. The meteorological diurnal boundary is from 20:00 of the current day to 20:00 of the next day, excluding the hourly value at 20:00 of the current day; the hydrological diurnal boundary is from 00:00 of the current day to 00:00 of the next day, excluding the hourly value at 00:00 of the next day.
[0058] As an optional implementation, in step S1, the observation value field at the hour is named according to the order of the observation element type and the observation element's day boundary. All observation data fields within the day boundary period are stored in rows by hour, with each row starting with an hour identifier and adjacent observation values separated by spaces.
[0059] As an optional implementation, in step S4, when the data processing instruction is the data storage instruction, the hydrological and meteorological observation data to be processed is obtained, and the hydrological and meteorological observation data to be processed is stored based on the observation element information table to obtain the stored hydrological and meteorological observation data. Specifically, this includes the following steps.
[0060] S41: Based on the data storage instruction, acquire the hydrological and meteorological observation data to be processed.
[0061] S42: Perform data subpackaging and data verification on the hydrological and meteorological observation data to be processed to obtain the verified data.
[0062] S43: Parse the verified data to obtain the parsed observation information; the parsed observation information includes: observation station code, observation element name, observation time and observation value.
[0063] S44: Based on the parsed observation information and the observation element information table, store and update the hydrological and meteorological observation data to be processed to obtain the stored hydrological and meteorological observation data.
[0064] As an optional implementation, in step S44, the hydrological and meteorological observation data to be processed is stored and updated according to the parsed observation information and the observation element information table to obtain the stored hydrological and meteorological observation data, specifically including the following steps.
[0065] S441: Based on the observation element name in the parsed observation information, query and match the corresponding observation element type in the observation element information table.
[0066] S442: Based on the type of observation element queried and matched, determine whether to shift the date of the observation time in the parsed observation information to the date horizon, and obtain a first determination result, including the following two cases.
[0067] (1) If the first judgment result is yes, then add 1 day to the observation time in the parsed observation information to obtain the updated observation time.
[0068] (2) If the first judgment result is negative, the observation time in the parsed observation information is directly used as the updated observation time.
[0069] S443: Based on the updated observation time, the name of the observation element and the observation station code in the parsed observation information, query and determine whether the observation record for the day exists, and obtain a second judgment result, including the following two situations.
[0070] (1) If the second judgment result is yes, then read the data that has been stored in all observation data fields within the day's observation record during the day's boundary period.
[0071] (2) If the second judgment result is negative, then all observation data fields within the day period are initialized and filled according to the default data filling rules in the observation element information table.
[0072] S444: Based on the number of data bits, the number of decimal places, and the updated observation time in the observation element information table, calculate the storage location of the observed value in the parsed observation information within all observation data fields of the day cycle.
[0073] S445: Format the observed values in the parsed observation information according to the number of data bits and the number of decimal places to obtain formatted observation values.
[0074] S446: Based on the storage location, replace the formatted observation value in the corresponding storage location to update all observation data fields within the day period. At the same time, synchronously update the observation value field at the hour, the maximum data and corresponding observation time field within the day period, and the minimum data and corresponding observation time field within the day period to obtain the stored hydrological and meteorological observation data.
[0075] As an optional implementation, in step S5, when the data processing instruction is the data query and retrieval instruction, the stored hydrological and meteorological observation data is queried and retrieved based on the observation element information table to obtain the data query and retrieval result, specifically including the following steps.
[0076] S51: Based on the data query and retrieval instruction, determine the data query conditions; the data query conditions include the observation station code, the observation element name, the query date and / or the query type; the query type includes: hourly data, full minute data or specified minute data.
[0077] S52: Based on the name of the observed element, query the corresponding observed element type and data format in the observed element information table.
[0078] S53: Determine the corresponding date period based on the observation element type and the query date, and locate the observation record corresponding to the date period.
[0079] S54: Based on the query type, read the corresponding data from the observation record to obtain the data query result.
[0080] As an optional implementation, in step S54, according to the query type, the corresponding data in the observation record is read to obtain the data query result, specifically including the following three cases.
[0081] (1) When the query type is the hourly data, read the data in the observation value field corresponding to the hourly time in the observation record as the data query result.
[0082] (2) When the query type is the full minute data, read the data in all observation data fields within the day period of the observation record as the data query result.
[0083] (3) When the query type is the specified minute data, the data position is calculated according to the query date, the observation element day boundary and the data format, and the corresponding minute data is extracted from all observation data fields within the day boundary period according to the data position, as the data query result.
[0084] In an exemplary embodiment, to illustrate the technical solution provided by the present application in detail, the specific implementation process for acquiring and storing the corresponding observation data is described below using wind speed and wind direction observation elements as examples. It is easy to understand that the specific implementation process for acquiring and storing the observation data corresponding to other types of observation elements (such as air temperature, relative humidity, air pressure, rainfall, visibility, surface seawater temperature, surface seawater salinity, and tidal level) is the same.
[0085] The method for acquiring and storing hydrological and meteorological observation data mainly includes the following implementation steps.
[0086] Step 1: Create a standardized data table.
[0087] This application embodiment employs an automatic hydrological and meteorological observation system for a marine observation station. This system includes a field data acquisition system and a data center receiving and processing subsystem, which are connected. The field data acquisition system comprises a meteorological subsystem and a hydrological subsystem. Both subsystems transmit observation data to the data center receiving and processing subsystem once per minute via communication methods such as fiber optics, satellite, CDMA, or GPRS. The meteorological subsystem primarily observes data corresponding to various observational elements such as wind direction, wind speed, air temperature, relative humidity, air pressure, rainfall, and visibility. The data center receiving and processing subsystem serves as the carrier for data storage and retrieval. A database is created within the data center receiving and processing subsystem, and standardized data tables are established within this database, including the following steps.
[0088] Step 1.1: Naming the observation element table.
[0089] In this embodiment, the observation element types include meteorological observation elements and hydrological observation elements. Meteorological observation elements include wind direction, wind speed, air temperature, relative humidity, air pressure, rainfall, and visibility. Hydrological observation elements include surface seawater temperature, surface seawater salinity, and tidal level. The observation element table name refers to the name of a certain observation element in a table (such as a standardized data table and an observation element information table). Because wind direction and wind speed are correlated, they are stored in the same data table; that is, the table name for the wind speed and wind direction table is WI. The table names for other observation elements are named with two English letters: air temperature is AT, relative humidity is HU, air pressure is BP, rainfall is RN, visibility is VB, surface seawater temperature is WT, surface seawater salinity is SL, and tidal level is WL.
[0090] Step 1.2: Design the fields included in the standardized data table.
[0091] In this embodiment, the standardized data table adopts a unified field naming rule and storage structure, and each observation station and each day cycle corresponds to one record of observation data. The standardized data table includes fields such as observation station code, observation date, observation value at the hour, maximum data and corresponding observation time within the day cycle, minimum data and corresponding observation time within the day cycle, and all observation data within the day cycle.
[0092] The observation station code refers to the code of each ocean observation station or the code of the observation equipment. The field name is zhcode, the data type is 4 characters, and it is used to store the unique observation station code or observation equipment code for each ocean observation station. Among them, zhcode is the observation station code, which is used to identify the observation data of a specific ocean observation station or observation equipment.
[0093] The observation date refers to the specific observation time of the hydrological and meteorological observation data. The field name is sdate, the data type is date, and the stored content is yyyy-MM-dd, where sdate is the observation date, yyyy is the year, MM is the month, and dd is the day.
[0094] The hourly observation field refers to the observation values corresponding to each hour, and the data type is numeric. The hourly observation field of the wind speed and direction table WI includes 48 fields with field names WS21, WD21, WS22, WD22, WS23, WD23, WS00, WD0, WS01, WD01, ..., WS20, WD20. All of them are of numeric data type and correspond to the wind speed and direction data observed at 21:00, 22:00, 23:00, 00:00, ..., 20:00, respectively. The hourly observation fields for the temperature table (AT), relative humidity table (HU), barometer (BP), precipitation table (RN), and visibility table (VB) include 24 fields named "table_name+21", "table_name+22", "table_name+23", "table_name+00", ..., "table_name+20", all of which are numeric and correspond to observations at 21:00, 22:00, 23:00, 00:00, ..., 20:00 respectively. For example, the temperature table AT contains 24 fields: AT21, AT22, AT23, AT00, ..., AT20. Similarly, the hourly observation fields for the surface seawater temperature table (WT), surface seawater salinity table (SL), and tide table (WL) include 24 fields named "table_name+00", "table_name+01", ..., "table_name+23", all of which are numeric and correspond to observations at 00:00, 01:00, 02:00, ..., 23:00 respectively. For example, the surface seawater temperature table WT contains 24 fields: WT00, WT01, ..., WT23, etc.
[0095] The diurnal period refers to a 24-hour observation period. The meteorological diurnal period is the diurnal period corresponding to meteorological observation elements. In this embodiment, the meteorological diurnal period is set from 20:00 on the current day to 20:00 on the next day, excluding the hourly value at 20:00 on the current day. The hydrological diurnal period is the diurnal period corresponding to hydrological observation elements. In this embodiment, the hydrological diurnal period is set from 00:00 on the current day to 00:00 on the next day, excluding the hourly value at 00:00 on the next day.
[0096] The "Maximum Data and Corresponding Observation Time within a Diurnal Cycle" field refers to the maximum observed value and corresponding observation time collected within a diurnal cycle. The wind speed and direction table (WI) includes fields named ZWS, ZWD, and ZTM, representing the daily maximum wind speed, the wind direction corresponding to the daily maximum wind speed, and the observation time, respectively. ZWS and ZWD are data types, while ZTM is a 4-character type, storing content as HHMM. In HHMM, HH represents the hour corresponding to the observation time, and MM represents the minute corresponding to the observation time. The temperature table (AT), relative humidity table (HU), barometer (BP), precipitation table (RN), visibility table (VB), surface sea temperature table (WT), surface sea salinity table (SL), and tide table (WL) all include fields named MAXVL and MAXTM, corresponding to the daily maximum observed value and observation time, respectively. MAXVL is a data type, and MAXTM is a 4-character type, also storing content as HHMM.
[0097] The field "Minimum Data and Corresponding Observation Time within a Diurnal Cycle" refers to the minimum observed value and corresponding observation time collected within a diurnal cycle. This field is not included in the wind speed and direction table (WI). The fields for temperature (AT), relative humidity (HU), barometric pressure (BP), precipitation (RN), visibility (VB), surface sea temperature (WT), surface sea salinity (SL), and tides (WL) all include fields named MINVL and MINTM, corresponding to the daily minimum observed value and observation time, respectively. MINVL is a data type; MINTM is a 4-character type, and its stored content is also HHMM.
[0098] The "All Observational Data within a Regime Period" field refers to all observational values collected within a Regime Period, i.e., the full amount of observational data within the Regime Period. The field name is "data" and the data type is "text".
[0099] Step 2: Establish an information table of observation elements.
[0100] In this embodiment, the observation element information table includes the storage name (i.e., the observation element table name) of each observation element, the data format (including the number of data bits and decimal places, such as the maximum number of observation data bits and the number of decimal places), the observation element type (meteorological observation elements are represented by label 1, and hydrological observation elements are represented by label 2), the default data filling rule (e.g., when there is no observation, the last digit of the data filling value is filled with "8", and the other digits are filled with "9"), and the data access method (the specific method of data storage or query retrieval). The default data filling rule is as follows: in the wind speed and direction table WI, the "data filling value when there is no observation" is the combined value "998 99.8"; in other observation element tables, the "data filling value when there is no observation" is filled according to the "maximum number of observation data bits" and "decimal places" of that observation element. For example, the record corresponding to temperature in the observation element information table is: the observation element table name is AT, the maximum number of observation data bits is 5, the number of decimal places is 1, the data filling value when there is no observation is 999.8, and the observation element type is 1.
[0101] Step 3: Design the storage content for all observation data fields within the day period.
[0102] In this embodiment, the "data" field, representing all observation data within the day's time period, stores the minute-by-minute observation data (i.e., "data") for each observation element within the day's time period. The day's time period is divided into 24 hours. Hourly observation data is stored in one row, with the first two digits representing the hour of the observation, separated by "H:". There are 24 rows in total, each separated by a newline character. For hydrological observation elements, the first row starts at 00:00, and the first observation data corresponds to 00:00 within the day's time period. Each row stores 60 observation data points for the current observation hour after the ":", separated by spaces. For meteorological observation elements, the first row starts at 20:00, and the first observation data corresponds to 20:01 within the day's time period. In the wind speed and direction table (WI), each row stores 60 sets of observation data for the current observation hour in order of wind direction and speed after the ":", separated by spaces. For other meteorological observation elements, each row stores 60 observation data points for the current observation hour after the ":", separated by spaces. Figure 3 , Figure 4 and Figure 5 The data portion is stored in Notepad format, where... Figure 3 This shows a portion of the data storage for temperature observation elements on March 1, 2024. Figure 4 This shows a portion of the data storage for wind speed and direction observations on March 18, 2024. Figure 5 This shows a portion of the data storage for tide level observation elements on March 18, 2024.
[0103] Step 4: Generate the default content for storing all observation data fields within the International Date Line.
[0104] In this embodiment, the "data fill value when there is no observation" of the observation element is found in the observation element information table by the observation element table name, and according to the data default fill rule in step 2, the "data fill value when there is no observation" is used to replace all the observation values of 1440 minutes within the day period. Combined with the storage content designed in step 3, all observation data within the day period are generated.
[0105] Step 5: The data center receiving and processing subsystem receives, parses, and stores data.
[0106] Step 5.1: The field acquisition system sends data storage instructions and hydrological and meteorological observation data to be processed to the data center receiving and processing subsystem. The hydrological and meteorological observation data to be processed is in the form of data packets, including data packet header flags, observation station codes, observation element table names, observation time, observation values, data check codes, and data end flags. The observation values in the wind speed and wind direction data packets include real-time wind speed and wind direction observation values, while the observation values in other data packets include real-time observation values of the observation elements.
[0107] Step 5.2: After receiving the data, the data center receiving and processing subsystem uses the traditional summation and verification method to perform data packet division and verification, and obtain the verified data packet.
[0108] Step 5.3: Parse the verified data packet to obtain the observation station code, observation element table name, observation time and observation value.
[0109] Step 5.4: Query the observation element type in the observation element information table by the observation element table name. If the observation element type is equal to 1 (meteorological observation element) and the observation time is greater than 20:00, the observation time is assigned as the observation time plus 1 day.
[0110] Step 5.5: Data storage, specifically including the following steps.
[0111] Step 5.5.1: Observe the data storage situation of the feature table name that is not equal to WI, including the following steps.
[0112] (1) If the observation feature table name is not equal to WI, set the variable lsData to empty. lsData represents storing the full minute data of the data field. The variables MAXVL, MAXTM, MINVL, and MINTM are empty.
[0113] (2) Check the database for the existence of data by using the observation element table name, observation time (year, month, and day), and observation station code. If the data does not exist, generate the default content for storing all observation data fields within the day period as in step 4, and store it in the variable lsData. If the data exists, assign the content of the data field to the variable lsData, assign the value of the MAXVL field (maximum daily observation value) to the variable MAXVL, assign the value of the MAXTM field (the observation time corresponding to the maximum daily observation value) to the variable MAXTM, assign the value of the MINVL field (minimum daily observation value) to the variable MINVL, and assign the value of the MINTM field (the observation time corresponding to the minimum daily observation value) to the variable MINTM.
[0114] (3) Replace the data for the observation time in the variable lsData with the observation element table name, observation time, and observation value. When replacing the location, query the observation element information table for the maximum number of observation data bits, decimal places, and observation element type (1 represents meteorological observation element, 2 represents hydrological observation element) and store them in the variables MaxBit (maximum number of observation data bits), DecBit (decimal places of observation data), and Gclx (observation element type) respectively. If the observation element type Gclx is equal to 1, add 239 minutes to the observation time and assign it to the variable lsdatetime (standard time converted by the date offset). If the observation element type Gclx is not equal to 1, assign the observation time to the variable lsdatetime. Set the variables Rec_Hour (hour corresponding to the observation data) and Rec_Minute (minute corresponding to the observation data) to correspond to the hour and minute values of the variable lsdatetime respectively. Calculate the number of data bits per row: LineCount = MaxBit × 60 + 6, where LineCount represents the number of data bits per row and MaxBit represents the maximum number of observation data bits. Then, calculate the number of data bits preceding the replacement position in the row: CLBDataBit = Rec_Minute × (MaxBit + 1) + 5, where CLBDataBit represents the number of data bits preceding the replacement position in the row, i.e., the offset position within the row, and Rec_Minute represents the minute corresponding to the observed data. Next, calculate the number of data bits at the replacement position: ReplacePosition = Rec_Hour × LineCount + CLBDataBit, where ReplacePosition represents the number of data bits at the replacement position, i.e., the precise storage location of the data in the data field, and Rec_Hour represents the hour corresponding to the observed data. Then, format the observed data according to the "maximum number of data bits" and "decimal places" and assign the result to the variable VData, where VData represents the formatted observed value. Use the variable VData to replace the data in the variable lsData starting from the ReplacePosition position for the specified number of "maximum number of data bits," completing the data update for lsData.
[0115] (4) If the observed value is greater than the value of variable MAXVL or variable MAXVL is empty, the observed value is assigned to variable MAXVL, and the observation time in hours and minutes is assigned to variable MAXTM.
[0116] (5) If the observed value is less than the value of the variable MINVL or the variable MINVL is empty, the observed value is assigned to the variable MINVL, and the observation time in hours and minutes is assigned to the variable MINTM.
[0117] (6) If the observation time is the hour, two hours are taken and stored in the variable sHour, where sHour represents the hour portion of the observation time. The observed value will be used as the hourly data value. The hourly field name of the data table corresponding to this hourly time is: "Observation feature table name + variable sHour". For example: If the observation time is: 2026-01-28 10:00:00, the observation value is 10.9, the observation feature table name is "AT", then the sHour value is "10", the hourly field name is "AT10", and the corresponding hourly value is 10.9.
[0118] (7) Based on the observation station code and observation time, store the variables lsData, MAXVL, MAXTM, MINVL and MINTM in the data table corresponding to the observation feature table name in the database. If it is the hour, the observation data needs to be stored in the hour field.
[0119] Step 5.5.2: Observe the data storage status of the feature table name equal to WI, including the following steps.
[0120] (1) If the observation feature table name is equal to WI, set the variable lsData to empty, the variable ZWS to empty, the variable ZWD to empty, and the variable ZTM to empty.
[0121] (2) Check the database for the existence of data by using the observation element table name, observation time (year, month, and day), and observation station code. If the data does not exist, generate the default content for storing all observation data fields within the day period as in step 4, and store it in the variable lsData. If the data exists, assign the content of the data field to the variable lsData, assign the ZWS value (daily maximum wind speed) to the variable ZWS, assign the ZWD value (wind direction corresponding to the daily maximum wind speed) to the variable ZWD, and assign the ZTM value (observation time corresponding to the daily maximum wind speed) to the variable ZTM.
[0122] (3) Replace the data in the variable lsData with the observation element table name, observation time, and observation value. When replacing the location, add 239 minutes to the observation time and assign it to the variable lsdatetime. Set the variables Rec_Hour and Rec_Minute to correspond to the hour and minute values of the variable lsdatetime, respectively. Then calculate the number of data bits for each row: LineCount = MaxBit × 60 + 6. Then calculate the number of data bits before the row where the replacement position is located: CLBDataBit = Rec_Minute × (MaxBit + 1) + 5. Then calculate the number of data bits ReplacePosition where the replacement position is located: ReplacePosition = Rec_Hour × LineCount + CLBDataBit. Format the wind direction data with a maximum of 3 digits and 0 decimal places and assign it to the variable VData1, where VData1 represents the formatted wind direction value. Format the wind speed data with a maximum of 4 digits and 1 decimal place and assign it to the variable VData2, where VData2 represents the formatted wind speed value. Assign “VData1 + space + VData2” to the variable VData. Replace the number of "maximum observation bits" in lsData starting from the ReplacePosition position with VData to complete the lsData data update.
[0123] (4) If the wind speed value in the observation is greater than the variable ZWS or the variable ZWS is empty, assign the wind speed value in the observation to the variable ZWS, assign the wind direction value to the variable ZWD, and assign the hour and minute part of the observation time to the variable ZTM.
[0124] (5) If the observation time is the hour, two hours are taken and stored in the variable sHour. The observed value will be used as the hourly data value. The hourly field name corresponding to this hourly time in the "WI" data table is: "WS" + variable sHour, "WD" + variable sHour. For example, if the "observation time" is: 2026-01-28 10:00:00, and the wind speed and wind direction in the "observation value" are 10.9 and 97 respectively, then the sHour value is 10, the hourly field name is WS10 and WD10, and the corresponding hourly values are 10.9 and 97.
[0125] (6) Based on the observation station code and observation time, store the variables lsData, ZWS, ZWD and ZTM in the data table corresponding to the observation element table name in the database. If it is the hour, the observation data needs to be stored in the hour field.
[0126] Step 6: After storing the hydrological and meteorological observation data to be processed into the database of the data center receiving and processing subsystem, when it is necessary to query and retrieve the stored hydrological and meteorological observation data, the data is retrieved from the database of the data center receiving and processing subsystem according to the data query and retrieval instruction, and the data query and retrieval results are obtained, including the following steps.
[0127] Step 6.1: Obtain the hourly data, that is, the observation data at each hour.
[0128] First, define the query conditions, including the observation element table name, observation station code, and query time. Then, using the observation element table name, query the corresponding observation element information table for the observation element type. If the observation element type equals 1 (meteorological observation element), and the hourly time of the query is greater than 20:00, assign the query time plus one day. Next, query the database for the existence of the data using the observation element table name, query time (year, month, and day), and observation station code. If the data does not exist, return an empty string. If the data exists, and the observation element table name is not equal to "WI", retrieve the data corresponding to the hourly field of the observation element table name and the query time; this data is the query result. For example, if the observation element table name is "WT" and the query time is "2026-01-28 10:00:00", the query result will be the value corresponding to the field "WT10". If the observation element table name is "WI", retrieve the data corresponding to "WS" and the hourly field of the query time, and the data corresponding to "WD" and the hourly field of the query time; this data is the query result.
[0129] Step 6.2: Obtain full minute data, i.e., all observation data for a given day. First, determine the query conditions, including the observation feature table name, observation station code, and query time. Then, use the observation feature table name, query time (year, month, and day), and observation station code to check if the data exists in the database. If the data does not exist, return an empty string, indicating that the data is missing. If the data exists, retrieve the data corresponding to the "data" field; this data is the result of the data query.
[0130] Step 6.3: Obtain data for a specified minute, i.e., observation data at a specific minute.
[0131] First, the query conditions are determined, including the observation element table name, observation station code, and query time. Then, using the observation element table name, the maximum number of digits, decimal places, and observation element type (1 for meteorological observation elements, 2 for hydrological observation elements) are retrieved from the corresponding observation element information table and stored in variables MaxBit, DecBit, and Gclx, respectively. If the observation element type (Gclx) equals 1 (meteorological observation element) and the query time is greater than 20:00, the query time is assigned as the query time plus one day. The database is then checked for data existence using the observation element table name, query time (year, month, and day), and observation station code. If the data does not exist, an empty value is returned. If the data exists, the value corresponding to the "data" field is assigned to the variable VData. When the data exists, the minute time location is obtained and its value is retrieved. If the observation element type (Gclx) equals 1 (meteorological observation element), the query time is added to 239 minutes and assigned to the variable lsdatetime. Otherwise, the query time is assigned to the variable lsdatetime. Then, set the variables Rec_Hour and Rec_Minute to correspond to the hour and minute values of the variable lsdatetime, respectively. Calculate the query's LineCount value: LineCount = MaxBit × 60 + 6. Calculate the query's CLBDataBit value: CLBDataBit = Rec_Minute × (MaxBit + 1) + 5. Calculate the query's ReplacePosition value: ReplacePosition = Rec_Hour × LineCount + CLBDataBit. Take MaxBit characters from the ReplacePosition position in the variable VData and assign them to the variable Vresult. Vresult represents the final data result returned by the query, i.e., the data query result.
[0132] This application proposes a method for acquiring and storing hydrological and meteorological observation data. This method standardizes the field content of each observation element's data table in the database, making each observation element regular and facilitating the development of a unified data entry and acquisition interface. By establishing an observation element information table, the storage location, type, entry method, and query method of each observation element in the database can be queried. Furthermore, this application defines a unified entry method and a unified data acquisition method for observation elements. The interface is simple and highly scalable, facilitating the acquisition of various types of observation data. It simplifies the generation of minute data files, hourly data files, and monthly delayed report files, improving the processing efficiency of hydrological and meteorological observation data storage and acquisition.
[0133] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 6 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores hydrological and meteorological observation data to be processed. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for acquiring and storing hydrological and meteorological observation data.
[0134] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.
[0135] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.
[0136] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.
[0137] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.
[0138] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Moreover, the collection, use and processing of the relevant data are carried out in compliance with the relevant data protection laws and policies of the country where the location is located, and with the authorization granted by the owner of the corresponding device.
[0139] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).
[0140] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.
[0141] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0142] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for acquiring and storing hydrological and meteorological observation data, characterized in that, include: Establish standardized data tables according to the preset observation element types and observation element day boundaries; The standardized data table adopts a unified field naming rule and storage structure, and each observation station and each day cycle corresponds to one record of observation data. The standardized data table includes: observation station code, observation date, observation value at the hour, maximum data and corresponding observation time within the day cycle, minimum data and corresponding observation time within the day cycle, and all observation data within the day cycle. Based on the standardized data table, an observation element information table is established; the observation element information table is used to configure the storage name, data format, observation element type, default data filling rule, and data access method of each observation element. Receive data processing instructions; the data processing instructions include data storage instructions or data query and retrieval instructions. When the data processing instruction is the data storage instruction, the hydrological and meteorological observation data to be processed is obtained, and the hydrological and meteorological observation data to be processed is stored based on the observation element information table to obtain the stored hydrological and meteorological observation data. When the data processing instruction is the data query and retrieval instruction, the stored hydrological and meteorological observation data is queried and retrieved based on the observation element information table to obtain the data query and retrieval result.
2. The method for acquiring and storing hydrological and meteorological observation data according to claim 1, characterized in that, The types of observation elements include meteorological observation elements and hydrological observation elements. The meteorological observation elements include wind direction, wind speed, air temperature, relative humidity, air pressure, rainfall, and visibility. The hydrological observation elements include surface seawater temperature, surface seawater salinity, and tidal level. The observation element boundaries include meteorological boundaries and hydrological boundaries.
3. The method for acquiring and storing hydrological and meteorological observation data according to claim 1, characterized in that, The observation value field at the hour is named according to the order of the observation element type and the observation element's day boundary. All observation data fields within the day boundary period are stored in rows by hour, with each row starting with an hour identifier and adjacent observation values separated by spaces.
4. The method for acquiring and storing hydrological and meteorological observation data according to claim 1, characterized in that, When the data processing instruction is the data storage instruction, the hydrological and meteorological observation data to be processed is acquired, and based on the observation element information table, the hydrological and meteorological observation data to be processed is stored to obtain the stored hydrological and meteorological observation data, specifically including: Based on the data storage instructions, the hydrological and meteorological observation data to be processed is obtained; The hydrological and meteorological observation data to be processed is divided into data packets and verified to obtain verified data. The verified data is parsed to obtain the parsed observation information, which includes: observation station code, observation element name, observation time, and observation value. Based on the parsed observation information and the observation element information table, the hydrological and meteorological observation data to be processed is stored and updated to obtain the stored hydrological and meteorological observation data.
5. The method for acquiring and storing hydrological and meteorological observation data according to claim 4, characterized in that, Based on the parsed observation information and the observation element information table, the hydrological and meteorological observation data to be processed is stored and updated to obtain the stored hydrological and meteorological observation data, specifically including: Based on the observation element names in the parsed observation information, query and match the corresponding observation element types in the observation element information table; Based on the type of observation element queried and matched, determine whether to shift the date of day in the parsed observation information to the date horizon, and obtain the first determination result; If the first judgment result is yes, then add 1 day to the observation time in the parsed observation information to obtain the updated observation time; If the first judgment result is negative, then the observation time in the parsed observation information is directly used as the updated observation time; Based on the updated observation time, the name of the observation element and the observation station code in the parsed observation information, query and determine whether the observation record for the day exists, and obtain the second judgment result; If the second judgment result is yes, then read the data that has been stored in all observation data fields within the day's observation record within the day's boundary period; If the second judgment result is negative, then all observation data fields within the day period are initialized and filled according to the default data filling rules in the observation element information table; Based on the number of data bits, the number of decimal places, and the updated observation time in the observation element information table, calculate the storage location of the observed value in the parsed observation information in all observation data fields within the day period; The observed values in the parsed observation information are formatted according to the number of data bits and the number of decimal places to obtain formatted observation values; Based on the storage location, the formatted observation values are replaced in the corresponding storage location to update all observation data fields within the day period. At the same time, the observation value field at the hour, the maximum data and corresponding observation time field within the day period, and the minimum data and corresponding observation time field within the day period are updated synchronously to obtain the stored hydrological and meteorological observation data.
6. The method for acquiring and storing hydrological and meteorological observation data according to claim 1, characterized in that, When the data processing instruction is the data query and retrieval instruction, based on the observation element information table, a data query and retrieval is performed on the stored hydrological and meteorological observation data to obtain the data query and retrieval results, specifically including: Based on the data query and retrieval instruction, the data query conditions are determined; the data query conditions include the observation station code, the name of the observation element, the query date and / or the query type; the query type includes: hourly data, full minute data or specified minute data; Based on the observation element name, query the corresponding observation element type and data format in the observation element information table; The corresponding date period is determined based on the observation element type and the query date, and the observation record corresponding to the date period is located. Based on the query type, the corresponding data in the observation record is read to obtain the data query result.
7. The method for acquiring and storing hydrological and meteorological observation data according to claim 6, characterized in that, Based on the query type, the corresponding data in the observation record is read to obtain the data query results, specifically including: When the query type is the hourly data, the data in the observation value field corresponding to the hourly time in the observation record is read as the data query result. When the query type is the full minute data, the data in all observation data fields within the day period of the observation record is read as the data query result. When the query type is the specified minute data, the data position is calculated based on the query date, the observation element's day boundary, and the data format. Then, based on the data position, the corresponding minute data is extracted from all observation data fields within the day boundary period as the data query result.
8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes the computer program to implement the hydrological and meteorological observation data acquisition and storage method according to any one of claims 1-7.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the hydrological and meteorological observation data acquisition and storage method as described in any one of claims 1-7.
10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the hydrological and meteorological observation data acquisition and storage method as described in any one of claims 1-7.